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EggBlock: Design and Implementation of Solar Energy Generation and Trading Platform in Edge-Based IoT Systems with Blockchain

Authors
Kwak, SubinLee, JoohyungKim, JangkyumOh, Hyeontaek
Issue Date
Mar-2022
Publisher
MDPI
Keywords
solar energy generation; energy trading; auction theory; testbed; measurement study; Internet of Things; blockchain; reinforcement learning
Citation
SENSORS, v.22, no.6
Journal Title
SENSORS
Volume
22
Number
6
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/84056
DOI
10.3390/s22062410
ISSN
1424-8220
Abstract
In this paper, to balance power supplement from the solar energy's intermittent and unpredictable generation, we design a solar energy generation and trading platform (EggBlock) using Internet of Things (IoT) systems and blockchain technique. Without a centralized broker, the proposed EggBlock platform can promote energy trading between users equipped with solar panels, and balance demand and generation. By applying the second price sealed-bid auction, which is one of the suitable pricing mechanisms in the blockchain technique, it is possible to derive truthful bidding of market participants according to their utility function and induce the proceed transaction. Furthermore, for efficient generation of solar energy, EggBlock proposes a Q-learning-based dynamic panel control mechanism. Specifically, we set the instantaneous direction of the solar panel and the amount of power generation as the state and reward, respectively. The angle of the panel to be moved becomes an action at the next time step. Then, we continuously update the Q-table using transfer learning, which can cope with recent changes in the surrounding environment or weather. We implement the proposed EggBlock platform using Ethereum's smart contract for reliable transactions. At the end of the paper, measurement-based experiments show that the proposed EggBlock achieves reliable and transparent energy trading on the blockchain and converges to the optimal direction with short iterations. Finally, the results of the study show that an average energy generation gain of 35% is obtained.
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